Topology based Infrastructure for Medical Emergency Coordination

Recent terrorist attacks and natural disasters have forced humanity to respond to crisis situations as effectively as possible. In these situations, especially the first hours, t he number of injured people exceeds the capability of a treatment facility and rescue workers cannot always rely on the existing communication infrastructure. This paper presents a coordination strategy for scheduling doctors to casualties in a crisis area, which uses an algorithm inspired by behaviour of ants in nature. Taking care of the distribution of victims in the field and their priority corresponding to the severity of the injuries, the proposed strategy optimizes the maximum number of lives saved. The necessary data is collected using electronic triage tags wi reless connected in a Mobile Ad-Hoc Network (MANET). In order to facilitate the necessary functionalities the nodes are org anized in a special topology and the communication between them takes place via a distributed blackboard structure.

[1]  Roberto Montemanni,et al.  A new algorithm for a Dynamic Vehicle Routing Problem based on Ant Colony System , 2002 .

[2]  Paul H. Calamai,et al.  An Experimental Study of a Simple Ant Colony System for the Vehicle Routing Problem with Time Windows , 2002, Ant Algorithms.

[3]  Leslie Lenert,et al.  Information technology and emergency medical care during disasters. , 2004, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[4]  Enrico L Quarantelli,et al.  Problematical aspects of the information/ communication revolution for disaster planning and research: ten non‐technical issues and questions , 1997 .

[5]  Douglas A. Palmer,et al.  An Intelligent 802.11 Triage Tag For Medical Response to Disasters , 2005, AMIA.

[6]  Léon J. M. Rothkrantz,et al.  Ant Based Mechanism for Crisis Response Coordination , 2006, ANTS Workshop.

[7]  A. Garner,et al.  Comparative analysis of multiple-casualty incident triage algorithms. , 2001, Annals of emergency medicine.

[8]  Hartmut Schmeck,et al.  An Ant Colony Optimization approach to dynamic TSP , 2001 .

[9]  Amy L. Murphy,et al.  LIME: Linda meets mobility , 1999, Proceedings of the 1999 International Conference on Software Engineering (IEEE Cat. No.99CB37002).

[10]  Leslie Lenert,et al.  802.11 Wireless Infrastructure To Enhance Medical Response to Disasters , 2005, AMIA.

[11]  C. Schultz,et al.  Disaster Triage: START, then SAVE—A New Method of Dynamic Triage for Victims of a Catastrophic Earthquake , 1996, Prehospital and Disaster Medicine.

[12]  M. Akay,et al.  The feasibility of using a forehead reflectance pulse oximeter for automated remote triage , 2004, IEEE 30th Annual Northeast Bioengineering Conference, 2004. Proceedings of the.

[13]  Susan McGrath,et al.  ARTEMIS Personal Area Networks for Emergency Remote Triage and Information Management , 2006 .

[14]  Loo Hay Lee,et al.  Heuristic methods for vehicle routing problem with time windows , 2001, Artif. Intell. Eng..

[15]  Paul Klapwijk Topology based Infrastructure for Crisis Situations , 2006 .

[16]  Patrick Dewilde,et al.  Design Considerations for an Infrastructure-Less Mobile Middleware Platform , 2005, BNAIC.

[17]  J. B. van Veelen,et al.  Effective and Efficient Coordination Strategies for Agile Crisis Response Organizations , 2006 .

[18]  Michael Guntsch,et al.  Applying Population Based ACO to Dynamic Optimization Problems , 2002, Ant Algorithms.